The present invention relates to robotics and, more particularly, to a method of applying knowledge from a human operator to a mobile slave expert machine via a master expert machine.
Robots are used for performing tasks in the factory at the production lines or a special purpose tasks in the laboratory or the like for full automation of the process. A traditional robotic system consists of:
a. The robot (for example a 6 degrees of freedom) PA1 b. The end effector (gripper) and tooling equipment PA1 c. Installation and the operator/programmer. PA1 1. A Master Expert Machine (MEM) for learning, and recording a professional task from a skilled worker and for calculating and processing appropriate parameters for a Slave Expert Machine. PA1 2. A Slave Expert Machine (SEM) for performing the single task whose parameters were obtained from the MEM. The SEM has a similar number of links as the MEM but less sensors & transmission means, less electronics and requires significantly less computing algorithms than the Master Expert Machine. Any number of SEMs can be located in the working areas without any physical or communication touch with the MEM. The Master--Slave concept opens a new robotic area for autonomous Expert Machines for a professional single tasked activity. PA1 1. Low cost--(50-80)% less than existing robots performing a similar task. The SEM's cost depends on various parameters as complexity of the repetitive task that it performs or on quantity and characteristics of its attached performance sensors which have a high valued contribution to the control complexity of the SEM. The cost varies between a minimum and maximum price: the minimum price includes limit switches and alarm sensory. The maximum price includes complete performance sensory in addition to limit switches and alarm sensory. A complete performance sensing is implemented via vision means (like TV camera), optical encoders, etc. A partial performance sensing may be implemented, for example, via a potentiometer instead of an optical encoder, sensed, for example, once per elementary move. PA1 2. The expert's machine "learning" process eliminates the overhead usually required for specific coding (custom software) for a given trajectory. There is no need for additional software in order to perform the SEM's task. PA1 3. There is no need of time for acclimating personnel to use the new machine, meaning the slave expert machine is an easy to operate apparatus by an inexperienced user. PA1 5. Will involve environmental and organizational positive consequences.
Installing a robotic system includes the developing of an end effector for the specific task and accessories needed for the automatic activity of the robot, in addition to the task programming of the robot. The robot's operator should be trained for several months, mostly at the robot's manufacturer place. Those facts cause a manual manufacturing of robots and massive integration & installation activity, leading to a very high cost of the robotic system, and explaining the missing mass production of robotic systems. For the same reasons, performing a professional task (only a skilled worker does) via the present equipment (traditional robotic systems) is a very complicated mission due to the complexity of the integration/controlling of the robot in such activity having clear economic consequences.
There exist known expensive robots of multi-tasking ability, with remarkable flexible reprogramming possibilities, for different tasks. Most types share common problems: high costs, operator training, specific coding (custom software), complicated final debug process at factory and high maintenance cost.